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Video based archival system encoding documents as QR frames in MP4 files. Features Git like version control, sub 100ms semantic search, LLM chat (OpenRouter), AES-256-GCM encryption, and streaming for multi GB files with constant 10MB memory.

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Pixelog

License: Apache 2.0 Go Version Go Report Card Build Status CLI Ready Security Format QR Encoding Vector Search Performance Version Control Streaming

A novel archival system that encodes documents as QR code frames in MP4 video files, enabling universal playback, Git-like version control, and sub-100ms semantic search.


What is Pixelog?

Pixelog transforms any document into a .pixe file - an MP4 video where each frame is a QR code containing chunks of your data. This approach unlocks:

  • Universal compatibility: MP4 plays on any device (phones, computers, TVs, browsers)
  • Git-like version control: Delta encoding tracks changes (64% space savings)
  • Sub-100ms semantic search: Vector embeddings enable meaning-based queries
  • Interactive LLM chat: RAG-powered Q&A with 200+ models via OpenRouter
  • Streaming architecture: Handle multi-GB files with constant 10MB memory
  • Military-grade encryption: AES-256-GCM with tamper detection
  • Air-gapped capable: Works completely offline

Technical Specs:

  • Format: MP4 with H.264-encoded QR frames
  • Density: 2.9KB per frame @ 1080p (87KB/sec)
  • Error correction: Reed-Solomon (30% damage tolerance)
  • Search: HNSW vector index with cosine similarity

Quick Start

Installation

go install github.com/ArqonAi/Pixelog/cmd/pixe@latest

Or build from source:

git clone https://github.com/ArqonAi/Pixelog.git
cd Pixelog
go build -o pixe ./cmd/pixe

Basic Workflow

# Convert document to .pixe format
pixe convert document.txt -o doc.pixe

# Build semantic search index
export OPENROUTER_API_KEY=sk-or-v1-xxx
pixe index doc.pixe

# Search by meaning
pixe search doc.pixe "machine learning concepts" --top 5

# Chat with your document
pixe chat doc.pixe

Core Features

File Operations

  • Convert any file type to .pixe format
  • Extract original files from .pixe archives
  • Display file metadata and structure
  • Integrity checking via SHA-256 hashing
  • AES-256-GCM encryption with password

Semantic Search

  • Build vector embeddings for sub-100ms search
  • Meaning-based queries (not just keyword matching)
  • Interactive LLM Q&A with automatic context retrieval
  • Ranked results by cosine similarity

Version Control

  • Create version snapshots with messages
  • List all versions with timestamps
  • Compare versions (frame-level changes)
  • Time-travel search across historical versions
  • Delta encoding (64% average space savings)

Performance

  • Sub-100ms search with HNSW indexing
  • Constant 10MB memory footprint (any file size)
  • Streaming support for multi-GB files
  • Parallel frame encoding/decoding

Security

  • AES-256-GCM authenticated encryption
  • PBKDF2 key derivation (600,000 iterations)
  • Reed-Solomon error correction (30% damage tolerance)
  • SHA-256 frame hashing for tamper detection
  • Air-gapped operation (no internet required)

CLI Commands

Basic Operations

pixe convert <input> -o <output.pixe>    # Convert to .pixe
pixe extract <file.pixe> -o <output>      # Extract from .pixe
pixe info <file.pixe>                     # Show file info
pixe verify <file.pixe>                   # Verify integrity

Semantic Search (requires OpenRouter API key)

export OPENROUTER_API_KEY=sk-or-v1-xxx
pixe index <file.pixe>                           # Build index
pixe search <file.pixe> "query" --top 5          # Search
pixe chat <file.pixe>                            # Interactive chat
pixe chat <file.pixe> --model openai/gpt-5       # Specific model
pixe chat <file.pixe> --list                     # Show models

Version Control

pixe version <file.pixe> -m "message"            # Create version
pixe versions <file.pixe>                        # List versions
pixe diff <file.pixe> <v1> <v2>                 # Compare versions
pixe query <file.pixe> <version> "query"         # Time-travel query

Encryption

pixe convert file.txt -o file.pixe --encrypt --password mypass
pixe extract file.pixe -o output --password mypass
pixe index file.pixe --password mypass

Use Cases

Knowledge Base Management

# Create and index
pixe convert docs/ -o knowledge.pixe
pixe index knowledge.pixe

# Semantic search
pixe search knowledge.pixe "authentication best practices"

# Track changes
pixe version knowledge.pixe -m "Added security section"
pixe diff knowledge.pixe 1 2

Compliance & Audit Trails

# Encrypted archive
pixe convert compliance-docs/ -o audit.pixe --encrypt --password xxx

# Track all changes
pixe versions audit.pixe

# Time-travel query
pixe query audit.pixe 1 "Q1 data retention policy"

# Verify integrity
pixe verify audit.pixe --password xxx

Research Paper Collections

# Index papers
pixe convert papers/ -o research.pixe
pixe index research.pixe

# Semantic citation search
pixe search research.pixe "transformer attention mechanisms"

# Chat with research
pixe chat research.pixe

Secure Document Archival

# Encrypted, air-gapped storage
pixe convert classified/ -o vault.pixe --encrypt --password xxx
pixe verify vault.pixe --password xxx
pixe extract vault.pixe -o restored/ --password xxx

Large-Scale Code Archival

# Streaming for multi-GB codebases
pixe convert monorepo.tar.gz -o codebase.pixe
# Auto-streaming: 2.5 GB with 10MB RAM

# Version control
pixe version codebase.pixe -m "Release v2.0"

# Semantic code search
pixe search codebase.pixe "authentication middleware"

How It Works

Architecture

Document → Chunks (2.9KB) → Encryption → QR Codes → MP4 Frames → .pixe File

Each .pixe file is an MP4 video:

  • Frame 0: Metadata (file info, encryption params, version history)
  • Frame 1+: QR-encoded data chunks
  • Audio track: Silent (required for MP4 spec)

Directory Structure

pixelog/
├── cmd/pixe/              # CLI (12 commands)
├── internal/
│   ├── converter/         # Document → .pixe
│   ├── crypto/            # AES-256-GCM
│   ├── qr/                # QR generation
│   ├── video/             # MP4 creation/extraction
│   ├── index/             # Semantic search
│   │   ├── indexer.go    # HNSW vector index
│   │   ├── embedder.go   # OpenRouter embeddings
│   │   └── delta.go      # Version control
│   └── llm/               # LLM client (OpenRouter)
├── pkg/config/            # Configuration
├── docs/                  # Documentation
└── examples/              # Usage examples

Performance

Operation Time Notes
Index Build 136ms One-time per file
Semantic Search <100ms With 1000+ frames
Frame Extraction 20ms Direct FFmpeg seek
LLM Chat Response <200ms Excl. LLM latency
Version Creation 85ms Delta calculation
Integrity Check 50ms/frame Parallel decoding

Storage Efficiency

  • Delta encoding: 64% space savings
  • GZIP compression: 75% reduction
  • Combined: ~80% smaller than raw storage

Memory Efficiency

File Size Traditional Pixelog Streaming
10 MB 10 MB RAM 10 MB RAM
100 MB 100 MB RAM 10 MB RAM
1 GB 1 GB RAM 10 MB RAM
10 GB 10 GB RAM 10 MB RAM

Streaming auto-enables for files >100MB.


Security

Encryption

  • Algorithm: AES-256-GCM (authenticated encryption)
  • Key Derivation: PBKDF2 (600,000 iterations, SHA-256)
  • Salt: 32-byte random per file
  • Nonce: 12-byte random per operation
  • Auth Tag: 16-byte for tamper detection

Error Correction

  • Reed-Solomon codes: 30% damage tolerance per frame
  • QR Error Correction: Level H (highest)
  • Data recovery: Even if portions of video corrupted

File Structure

.pixe File (MP4 Container)
├── Video Track (H.264)
│   ├── Frame 0: Metadata
│   ├── Frame 1+: [32B salt][12B nonce][encrypted data][16B auth tag]
└── Audio Track (silent)

LLM Integration

OpenRouter API

Pixelog uses OpenRouter for embeddings and LLM chat (200+ models, one API key).

Get free key: https://openrouter.ai/keys

export OPENROUTER_API_KEY=sk-or-v1-xxx

Top 10 Models

Rank Model Cost Speed Description
1 DeepSeek R1 $0.14/1M Fast Best value (default)
2 Gemini 2.5 Flash FREE Very Fast Latest Google, free
3 Gemini 2.5 Pro $0.50/1M Medium Best Gemini
4 GPT-5 $2.50/1M Medium Latest OpenAI
5 Claude 4.5 Sonnet $3.00/1M Medium Best reasoning
6 Grok 3 $5.00/1M Fast Real-time data
7 Llama 3.3 70B $0.18/1M Fast Open source
8 Qwen 2.5 72B $0.18/1M Fast Multilingual
9 Mistral Large $2.00/1M Fast European
10 GPT-4o $0.75/1M Fast Multimodal

Usage

# List models
pixe chat doc.pixe --list

# Default (DeepSeek R1)
pixe chat doc.pixe

# Free tier (Gemini)
pixe chat doc.pixe --model google/gemini-2.5-flash-latest

# Premium (GPT-5)
pixe chat doc.pixe --model openai/gpt-5

Costs

Operation Model Cost Notes
Embeddings (indexing) text-embedding-3-large $0.02/1M One-time
Search queries text-embedding-3-large $0.0001/query Per query
Chat (default) deepseek/deepseek-r1 $0.14/1M Best value
Chat (free) gemini-2.5-flash FREE Free tier

Example: Index 1,000 docs ($2) + 10,000 searches ($1) + 1M tokens chat ($0.14 or FREE)


FAQ

Why video-based storage?

  1. Universal compatibility: MP4 plays everywhere
  2. Built-in streaming: Progressive loading
  3. Frame-level access: Direct seek without loading full file
  4. Visual inspection: See data as scannable QR codes
  5. Novel use cases: Video-based data transmission

Do I need an API key?

Optional. Core operations work offline:

  • Convert, extract, verify, version control: No API needed

Required for:

  • Semantic search (indexing + search)
  • LLM chat

Get free key: https://openrouter.ai/keys

How secure is it?

Military-grade: AES-256-GCM encryption, same as classified government systems.

  • 600,000 PBKDF2 iterations (brute-force protection)
  • Authenticated encryption (tamper detection)
  • Air-gapped operation (works offline)
  • Suitable for HIPAA, SOC 2, ISO 27001

Can I use it offline?

Yes, most features:

  • Offline: Convert, extract, encrypt/decrypt, verify, version control
  • Online: Semantic search, LLM chat (requires OpenRouter API)

How large can files be?

No practical limit due to streaming:

  • Small files (<100MB): Loaded into memory
  • Large files (>100MB): Auto-streaming mode
  • Memory: Constant 10MB footprint
  • Tested: Up to 10GB files

What file types?

All types: Documents, code, archives, media, databases, binaries. Pixelog is format-agnostic.

How fast is search?

Sub-100ms:

  • Index build: 136ms (one-time)
  • Search query: <100ms (1000+ frames)
  • Total: Query → Results in <100ms

API & Library Usage

package main

import (
    "github.com/ArqonAi/Pixelog/internal/converter"
    "github.com/ArqonAi/Pixelog/internal/index"
    "github.com/ArqonAi/Pixelog/internal/llm"
)

func main() {
    // Convert
    conv, _ := converter.New("./output")
    conv.ConvertFile("doc.txt", &converter.ConvertOptions{
        OutputPath:    "doc.pixe",
        EncryptionKey: "password",
    })

    // Index
    embedder := index.NewSimpleEmbedder("openrouter", apiKey, "auto")
    indexer, _ := index.NewIndexer("./indexes", embedder)
    idx, _ := indexer.BuildIndex("doc", "doc.pixe")

    // Search
    results, _ := indexer.Search(idx, "query", 5)

    // Version control
    deltaManager, _ := index.NewDeltaManager("./deltas", indexer)
    deltaManager.CreateVersion("doc", "doc.pixe", "Initial", "user")

    // LLM chat
    client := llm.NewClient("deepseek/deepseek-r1", apiKey)
    response, _ := client.Chat("Explain main concepts")
}

Contributing

See CONTRIBUTING.md

git checkout -b feature/amazing-feature
./test_e2e.sh
git commit -m "feat: Add amazing feature"
git push origin feature/amazing-feature

License

Apache License 2.0 - see LICENSE


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Turn documents into videos. Search at the speed of thought. Track changes like Git. Chat with AI.

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Video based archival system encoding documents as QR frames in MP4 files. Features Git like version control, sub 100ms semantic search, LLM chat (OpenRouter), AES-256-GCM encryption, and streaming for multi GB files with constant 10MB memory.

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